• Proceedings of the KIEE Conference
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• 2005.11b
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• pp.46-48
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• 2005

This paper discusses a probabilistic method for power system security assessment. The security analysis relates to the ability of the electric power systems to survive sudden disturbances such as electric short circuits or unanticipated loss of system elements. It consists of both steady state and dynamic security analyses, which are not two separate issues but should be considered together. In steady state security analysis including voltage security analysis, the analysis checks that the system is operated within security limits by OPF (optimal power flow) after the transition to a new operating point. Until now, many utilities have difficulty in including dynamic aspects due to computational capabilities. On the other hand. dynamic security analysis is required to ensure that the transition may lead to an acceptable operating condition. Transient stability, which is the ability of power systems to maintain synchronism when subjected to a large disturbance. is a principal component in dynamic security analysis. Usually any loss of synchronism may cause additional outages and make the present steady state analysis of the post-contingency condition inadequate for unstable cases. This is the reason for the need of dynamic studies in power systems. Probabilistic criterion can be used to recognize the probabilistic nature of system components while considering system security. In this approach. we do not have to assign any predetermined margin of safety. A comprehensive conceptual framework for probabilistic static and dynamic assessment is presented in this paper. The simulation results of the Western System Coordinating Council (WSCC) system compare an analytical method with Monte-Carlo simulation (MCS).

• The Korean Journal of Applied Statistics
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• v.31 no.2
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• pp.287-301
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• 2018

It is common to encounter count data with excess zeros in various research fields such as the social sciences, natural sciences, medical science or engineering. Such count data have been explained mainly by zero-inflated Poisson model and extended models. Zero-inflated count data are also often correlated or clustered, in which random effects should be taken into account in the model. Frequentist approaches have been commonly used to fit such data. However, a Bayesian approach has advantages of prior information, avoidance of asymptotic approximations and practical estimation of the functions of parameters. We consider a Bayesian zero-inflated Poisson regression model with random effects for correlated zero-inflated count data. We conducted simulation studies to check the performance of the proposed model. We also applied the proposed model to smoking behavior data from the Regional Health Survey (2015) of the Korea Centers for disease control and prevention.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.4
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• pp.194-202
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• 2019

Reliability analysis of the components frequently starts with the data that manufacturer provides. If enough failure data are collected from the field operations, the reliability should be recomputed and updated on the basis of the field failure data. However, when the failure time record for a component contains only a few observations, all statistical methodologies are limited. In this case, where the failure records for multiple number of identical components are available, a valid alternative is combining all the data from each component into one data set with enough sample size and utilizing the useful information in the censored data. The ROK Navy has been operating multiple Patrol Killer Guided missiles (PKGs) for several years. The Korea Multi-Function Control Console (KMFCC) is one of key components in PKG combat system. The maintenance record for the KMFCC contains less than ten failure observations and a censored datum. This paper proposes a Bayesian approach with a Dirichlet mixture model to estimate failure time density for KMFCC. Trends test for each component record indicated that null hypothesis, that failure occurrence is renewal process, is not rejected. Since the KMFCCs have been functioning under different operating environment, the failure time distribution may be a composition of a number of unknown distributions, i.e. a mixture distribution, rather than a single distribution. The Dirichlet mixture model was coded as probabilistic programming in Python using PyMC3. Then Markov Chain Monte Carlo (MCMC) sampling technique employed in PyMC3 probabilistically estimated the parameters' posterior distribution through the Dirichlet mixture model. The simulation results revealed that the mixture models provide superior fits to the combined data set over single models.

• Journal of Communications and Networks
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• v.10 no.2
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• pp.137-147
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• 2008

This paper proposes a novel approach to interference avoidance via inter-cell relaying in cellular OFDMA-TDD (orthogonal frequency division multiple access - time division duplex) systems. The proposed scheme, termed asymmetry balancing, is targeted towards next-generation cellular wireless systems which are envisaged to have ad hoc and multi-hop capabilities. Asymmetry balancing resolves the detrimental base station (BS)-to-BS interference problem inherent to TDD networks by synchronizing the TDD switching points (SPs) across cells. In order to maintain the flexibility of TDD in serving the asymmetry demands of individual cells, inter-cell relaying is employed. Mobile stations (MSs) in a cell which has a shortage of uplink (UL) resources and spare downlink (DL) resources use free DL resources to off-load UL traffic to cooperating MSs in a neighboring cell using ad hoc communication. In an analogous fashion DL traffic can be balanced. The purpose of this paper is to introduce the asymmetry balancing concept by considering a seven-cell cluster and a single overloaded cell in the center. A mathematical model is developed to quantify the envisaged gains in using asymmetry balancing and is verified via Monte Carlo simulations. It is demonstrated that asymmetry balancing offers great flexibility in UL-DL resource allocation. In addition, results show that a spectral efficiency improvement of more than 100% can be obtained with respect to a case where the TDD SPs are adapted to the cell-specific demands.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.9
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• pp.1931-1942
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• 2002

In this paper a formulation of robust optimization is presented and illustrated by a design example of vibratory micro gyroscopes in order to reduce the effect of variations due to uncertainties in MEMS fabrication processes. For the vibratory micro gyroscope considered it is important to match the resonance frequencies of the vertical (sensing) and lateral (driving) modes as close as possible to attain a high sensing sensitivity. A deterministic optimization in which the difference of both the sensing and driving natural frequencies is minimized as an objective function results in highly enhanced performance but apt to be very sensitive to fabrication errors. The formulation proposed is to attain robustness of the performance by including the sensitivity of the response with respect to uncertain variables as a term of objective function to be minimized. This formulation is simple and practically applicable since no detail statistical information on fabrication errors is required. The geometric variables, beam width, length and thickness of vibratory micro gyroscopes are adopted as design variables and at the same time considered as uncertain variables because here occur the fabrication errors. A robustness test in terms of a percentage yield by using the Monte Carlo simulation has shown that the robust optimum produces twice more acceptable designs than the deterministic optimum. Improvement of robustness becomes bigger as the amount of fabrication errors is assumed larger. Considering that the magnitude of fabrication errors and uncertainties in a MEMS structure are comparatively large, the present method is illustrated to be a viable approach for a robust MEMS design.

• Geomechanics and Engineering
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• v.20 no.1
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• pp.43-54
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• 2020

The limit analysis and response surfaces method were combined to investigate the reliability of pressurized tunnel faces subjected to seismic force. The quasi-static method was utilized to introduce seismic force into the tunnel face. A 3D horn failure mechanism of pressurized tunnel faces subjected to seismic force was constructed. The collapse pressure of pressurized tunnel faces was solved by the kinematical approach. The limit state equation of pressurized tunnel faces was obtained according to the collapse pressure and support pressure. And then a reliability model of pressurized tunnel faces was established. The feasibility and superiority of the response surfaces method was verified by comparing with the Monte Carlo method. The influence of the mean of soil parameters and support pressure, variation coefficients, distribution type and correlation of c-φ on the reliability of pressurized tunnel faces was discussed. The reasonable safety factor and support pressure required by pressurized tunnel faces to satisfy 3 safety levels were presented. In addition, the effects of horizontal seismic force, vertical seismic force and correlation of k_h-k_v on the reliability of pressurized tunnel faces were also performed. The method of this work can give a new idea for anti-seismic design of pressurized tunnel faces.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.4 no.2
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• pp.13-19
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• 2008

In order to predict a remaining life of a plant, it is necessary to select the components that are critical to the plant life. The remaining life of those components shall be evaluated by considering the aging effect of materials used as well as numerous factors. However, when evaluating reliability of nuclear structural components, some problems are quite formidable because of lack of information such as operating history, material property change and uncertainty in damage models. Accordingly, if structural integrity and safety are evaluated by the deterministic fracture mechanics approach, it is expected that the results obtained are too conservative to perform a rational evaluation of plant life. The probabilistic fracture mechanics approaches are regarded as appropriate methods to rationally evaluate the plant life since they can consider various uncertainties such as sizes and shapes of cracks and degradation of material strength due to the aging effects. The objective of this study is to evaluate the structural integrity for a reactor pressure vessel under the small break loss of coolant accident by applying the deterministic and probabilistic fracture mechanics. The deterministic fracture mechanics analysis was performed using the three dimensional finite element model. The probabilistic integrity analysis was based on the Monte Carlo simulation. The selected random variables are the neutron fluence on the vessel inside surface, the content of copper, nickel, and phosphorus in the reactor pressure vessel material, and initial RTNDT.

• Economic and Environmental Geology
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• v.33 no.4
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• pp.295-307
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• 2000

Probabilistic analysis is a powerful method to quantify variability and uncertainty common in engineering geology fields. In rock slope engineering, the uncertainty and variation may be in the form of scatter in orientations and geometries of discontinuities, and also test results. However, in the deterministic analysis, the factor of safety which is used to ensure stability of rock slopes, is based on the fixed representative values for each parameter without a consideration of the scattering in data. For comparison, in the probabilistic analysis, these discontinuity parameters are considered as random variables, and therefore, the reliability and probability theories are utilized to evaluate the possibility of slope failure. Therefore, in the probabilistic analysis, the factor of safety is considered as a random variable and replaced by the probability of failure to measure the level of slope stability. In this study, the stochastic properties of discontinuity parameters are evaluated and the stability of rock slope is analyzed based on the random properties of discontinuity parameters. Then, the results between the deterministic analysis and the probabilistic analysis are compared and the differences between the two analysis methods are explained.

• Journal of the Society of Naval Architects of Korea
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• v.33 no.1
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• pp.98-108
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• 1996

In the reliability analysis of general structures, the limit state equations are implicit and cannot be described in closed form. Thus, sampling methods such as the Crude Monte-Carlo simulation, and probabilistic FEM are often used, but these methods are not so effective in view of computational cost, because a number of structural analysis are required and the derivatives must be calculated for probabilistic FEM. Alternatively the response surface approach, which approximates the limit state surface by using several results of structural analysis in the region adjacent to MPFP, could be applied effectively. In this paper, the central composite design, Bucher-Bourgund method and the approximation method using artificial neural network are studied for the calculation of probability of failure by the response surface method. Through the example comparisons, it is found that Bucher-Bourgund method is very effective and Neural network method for the reliability analysis is comparable with other methods. Specially, the central composite design method is found to be rational and useful in terms of mathematical consistency and accuracy.

• Journal of Environmental Health Sciences
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• v.40 no.5
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• pp.397-406
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• 2014

Objectives: Perchloroethylene (PCE) is a volatile chemical widely used as a solvent in the dry-cleaning and textile processing industries. It was evaluated as Group 2 "probably carcinogenic to humans" by the Integrated Risk Information System (IRIS) of the United State Environmental Protection Agency (U.S. EPA) in 2012. In order to provide a scientific basis for establishing risk management measures for chemicals on the national priority substances list, aggregate risk assessment was conducted for PCE, included in the top-10 substances. Methods: We conducted the investigation and monitoring of PCE exposure (e.g., exposure scenario, detection levels, and exposure factors, etc.) and assessed its multi-media (e.g., outdoor air, indoor air, and ground water) exposure risk with a deterministic and probabilistic approach. Results: In human risk assessment (HRA), the level of human exposure was higher in the younger age group. The exposure level through inhalation at home was the highest among the exposure routes. Outdoor air or uptake of drinking water represented less than 1% of total contributions to PCE exposure. These findings suggested that the level of risk was negligible since the Hazard Index (HI) induced by HRA was below one among all age groups, with a maximum HI value of 0.17 when reasonable maximum exposure was applied. Conclusion: In conclusion, it was suggested that despite low exposure risk, further studies are needed considering main sources, including occupational exposure.